1 Introduction
The analysis in the report is regarding building certification lodgements in the Townsville local government area. Townsville is a city and a major port area in eastern Queensland, Australia. Two data sets have been combined and used for the analysis from the www.data.gov.au website.
First data set i.e. the building approval details have been extracted from here (“Townsville City Council Building Approvals - data.gov.au”, 2021) and includes number of building approvals from 2009 to 2021 and their corresponding details e.g. Decision, Class, Suburb etc. And the second data set i.e. City of Townsville’s Suburb geometry has been extracted from here (“Townsville Suburbs - data.gov.au.”, 2021) and includes the geometrical values for these Suburbs.
This report has been complied using R Studio (“RStudio Team”, 2020), Github (“GitHub: Where the world builds software”, 2021), Gitkraken(“GitKraken Documentation”, 2021) and Atom(“A hackable text editor for the 21st Century”, 2021).
Project Details
Name: Analyzing Building approvals data for the City of Townsville (Assignment 4, ETC5513)
Objective: Answering research questions regarding Year, Approvals, Class, Category, Suburb and Estimated Cost for Building Approvals in the city of Townsville.
Research Questions
To identify the year with maximum approvals and to analyze the data further to find out the suburb and estimate cost of building with respect to the most popular class in that year. And also find out the category that is most in demand for that class.
To analyze the suburb which was inferred from research question 1 and find out the year for which it had the maximum approvals. Also find out the class that occurred maximum times, category with respect to that class and estimate cost for these particular variables.
2 Analysis
(Please use plotly (Click on the figure/table to active plotly) to hover through the figures/tables and maps for better understanding of the analysis)
Variable Names
After data cleaning according to our research questions, we will be selecting the following variables:
| Application Type |
| Date Of Decision Notice |
| Decision |
| Class |
| Subcategory |
| Category |
| Estimated Cost |
| Suburb |
| Latitude |
| Longitude |
For table 2.1, the description of the variables used in the data set:
Application type: Here, application for ‘building certification lodgements’.
Date of decision notice: The date the building certifier made a notice that the works met the building codes.
Decision: Current status of the works as recorded with Council.
Class: The building classification as per the list on page one.
Sub-category (Council category descriptors): This category is a subdivision of class. Provides information regarding additions, alterations, subdwell etc in it.
Category: Townsville City Council has published on its website for a number of years a summary of building approval data using the certain categories.
Estimated values: The monetary value of the proposed building work.
Suburb: The suburb where the building work is taking place.
Latitude and Longitude: Geometrical dimensions.
2.1 Answering Research Question 1.
2.1.1 Finding Year with maximum approvals as a decision, overall.
Figure 2.1: Year v/s Decision count
From the graph 2.1, we see that, finalized projects have maximum count, but we will consider the count of approved projects into consideration because:
Finalized projects are projects sent by architects to be approved by the regulation committee and the approved projects are the confirmed projects. Thus, it makes more sense to consider approved projects over finalized while deciding the best year.
- The year 2020 has maximum approvals till now.
2.1.2 Finding class occuring in maximum suburbs and finding its total count, for approved projects in 2020.
(Keeping, ‘Year as 2020’ and ‘Decision as Approved’, constant)
Figure 2.2: Distribution of class in Townsville’s subrub area’s
In figure (map) 2.2, using plotly, we observe that Class 1a occurs in maximum suburbs.
| Year | Class | Count_of_Class |
|---|---|---|
| 2020 | Class 1a | 406 |
| 2020 | Class 10a | 275 |
| 2020 | Class 10b | 154 |
| 2020 | Class 6 | 25 |
| 2020 | Class 5 | 13 |
| 2020 | Class 9b | 13 |
Table 2.2 gives us the total count of Class 1a. It shows that Class 1a has the maximum count out of all the other classes.
Class 1a includes :Single dwelling, detached house, town house or villa unit.
From figure 2.2 and table 2.2, we were able to find out that the class 1a occurs in most suburbs. Each suburbs can have multiple class 1a projects.
Not only does it occur in most of the suburbs, but also these projects have a maximum count among all other projects.
Therefore, Class 1a occurs for most areas and maximum no. of times for approved projects in the year 2020.
2.1.3 Finding category with maximum counts in Class 1a (approved projects), in 2020.
(Keeping, ‘Decision as Approved’ and ‘Class as 1a’, constant and showing variation for years and identifying category count for ‘Year 2020’)
Figure 2.3: Count v/s Category
In figure 2.3, by clicking on play, we observe that for half the years in the data set, Residential-Other category has been on the top and for the other half, Single Detached Dwelling-New has been in demand.
- Identifying for the year 2020, we see that out of Class 1a, Residential-Other category is most in demand out of approved projects in the year 2020.
2.1.4 Finding Suburb for Residential category (Class 1a), approved projects in 2020.
(Keeping, ‘Year as 2020’. ‘Decision as Approved’, ‘Class as 1a’ and ‘Category as Residential-Other’, constant)
Figure 2.4: Suburb v/s Approval Count
Figure 2.4 shows that suburbs Kirwan and Hermit Park have the maximum approval count.
- Therefore, the suburbs Kirwan and Hermit Park, have most no. of class 1a’s with category as Residential-Other in approved projects for 2020.
2.1.5 Estimated cost(x) for research question 1.
By (Keeping, ‘Year as 2020’. ‘Decision as Approved’, ‘Class as 1a’ and ‘Category as Residential-Other’, constant)
| x |
|---|
| 993644 |
Table 2.3 displays the cost for Kirwan in best year 2020.
| x |
|---|
| 1074668 |
Table 2.4 displays the cost for Hermit Park in best year 2020.
| x |
|---|
| 2068312 |
- Therefore by observing table 2.5, we know that the total cost for suburbs Kirwan and Hermit Park’s class 1a approved projects(Residential-Other category) in 2020 is $2,068,312
2.2 Answering Research Question 2.
2.2.1 Finding the Year for maximum approvals in Kirwan and Hermit Park.
(Keeping, ‘Decision as Approved’ and ‘Suburbs as Kirwan and Hermit Park’, constant)
Figure 2.5: Year v/s Approval Count with respect to Suburbs
- From 2.5, it is evident that for Kirwan, the maximum approvals occurred in 2021 and for Hermit Park, the year was 2020.
2.2.2 Finding class that occurs most no. of times for approved projects in Kirwan and Hermit Park, in 2021 and 2020 respectively.
(Keeping, ‘Decision as Approved’, ‘Suburbs as Kirwan and Hermit Park’, Year as 2021 (for Kirwan) and 2020 (for Hermit Park), constant)
| Year | Class | Suburb | Decision | Class_count |
|---|---|---|---|---|
| 2021 | Class 10a | Kirwan | #Approved | 31 |
| 2021 | Class 1a | Kirwan | #Approved | 13 |
| 2021 | Class 10b | Kirwan | #Approved | 8 |
| 2021 | Class 5 | Kirwan | #Approved | 2 |
| 2021 | Class 6 | Kirwan | #Approved | 1 |
| 2021 | Class 9b | Kirwan | #Approved | 1 |
- From 2.6 it is clear that Class 10a occurs for most no. of times for approved projects in Kirwan in 2021.
Class 10a includes : Private garage, carport or shed
| Year | Class | Suburb | Decision | Class_count |
|---|---|---|---|---|
| 2020 | Class 1a | Hermit Park | #Approved | 18 |
| 2020 | Class 10a | Hermit Park | #Approved | 4 |
| 2020 | Class 10b | Hermit Park | #Approved | 3 |
- From 2.7 it is clear that Class 1a occurs for most no. of times for approved projects in Hermit Park in 2020.
Class 1a having maximum count matches with table 2.2, where also, Class 1a had maximum count in 2020.
2.2.3 Out of Class 10a and Class 1a, finding category that is most in demand for approved projects in Kirwan(2020) and Hermit Park(2021) respectively.
(Keeping, ‘Decision as Approved’,‘Suburbs as Kirwan and Hermit Park’,constant. Keeping ‘Year as 2021’ and ‘Class as 10a’ constant for Kirwan. Keeping ‘Year as 2020’ and ‘Class as 1a’ constant for Hermit Park.)
Figure 2.6: Count of Categories for their respective Suburbs and Class
The figure 2.6 displays two polar graphs with category count in Kirwan(left) and category count in Hermit Park(right).
- It is evident from both the graphs that the Residential-Other category for approved projects, is in demand for both suburbs and both classes in their respective years.
2.2.4 Estimated cost(x) for research question 2.
(Keeping, ‘Decision as Approved’, ‘Category as Residential-Other’,‘Suburbs as Kirwan and Hermit Park’,constant. Keeping ‘Year as 2021’ and ‘Class as 10a’ constant for Kirwan. Keeping ‘Year as 2020’ and ‘Class as 1a’ constant for Hermit Park.)
| x |
|---|
| 511371 |
Table 2.8 displays the cost for Kirwan in 2021.
| x |
|---|
| 1074668 |
Table 2.9 displays the cost for Hermit Park in best year 2020. And this observation is similar to table 2.4.
Therefore by observing table 2.8, we know that the total cost for suburb Kirwan for class 10a approved projects(Residential-Other category) in 2020 is $511,371.
And from 2.9, we know that the total cost for suburb Hermit Park for class 1a approved projects(Residential-Other category) in 2021 is $1,074,668.
3 Conclusion :
3.1 Result 1:
3.1.1 The result for the first research question is depicted below:
Figure 3.1: Result 1 Flowchart
Figure (flowchart) 3.1 depicts the step-wise-step results for research question 1.
We observed that the end product of result 1 gives us two suburbs with maximum residential category in class 1a for approved projects in the year 2020.
Further we carried out a reverse analysis for the resulting suburbs in question 1 i.e. for Kirwan and Hermit Park.
3.2 Result 2:
3.2.1 The result for the research question 2, Part A (Reverse analysis for Kirwan) is depicted below:
Figure 3.2: Result 2, Part A Flowchart
Figure (flowchart) 3.2 displays the reverse analysis for result 1, for Kirwan Suburb.
Here, we observe that, only the Residential-Other category is common between flowchart 3.1 and flowchart 3.2 i.e. in our best year 2020, Residential category was maximum and the same is in the case of Kirwan.
Hence, we can say that, for research question 2, Part A: Since the year 2021 has not ended, there is a possibility that for research question 1, maximum approvals happen in 2021, instead of 2020, making 2021 as the best year. And then further by doing reverse analysis from the results of research question 1 , we might get a similar flowchart for both Result 1 and Result 2 (Part A)
3.2.2 The result for the research question 2, Part B (Reverse analysis for Hermit Park) is depicted below:
Figure 3.3: Result 2, Part B Flowchart
Figure (flowchart) 3.3 displays the reverse analysis for result 1, for Hermit Park Suburb.
Here, we observe that, all the components for Hermit Park are common between flowchart 3.1 and flowchart 3.3. In both the flowcharts, best (maximum approvals) year 2020, project Class 1a, category residential-other and cost $1,074,668 are common.
We can say that, for research question 2, Part B: the reverse Analysis for result 1 has been successful
3.3 Final Result
Although, out of the approvals that took place in the year 2020 (best year with maximum approvals), maximum approvals were of Kirwan, but this has not been the case vice-versa and hence there is not much similarity between result 1 and result 2(PartA).
For result 1 and result 2(Part B), both the flowcharts are depicting the reverse of each other, giving the same information.
4 References
[1] D. Kahle and H. Wickham. ggmap: Spatial Visualization with ggplot2. The R Journal, 5(1), 144-161. URL http://journal.r-project.org/archive/2013-1/kahle-wickham.pdf
[2] Original S code by Richard A. Becker, Allan R. Wilks. R version by Ray Brownrigg. Enhancements by Thomas P Minka and Alex Deckmyn. (2018). maps: Draw Geographical Maps. R package version 3.3.0. https://CRAN.R-project.org/package=maps
[3] Hao Zhu (2021). kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax. R package version 1.3.4. https://CRAN.R-project.org/package=kableExtra
[4] Hadley Wickham and Jim Hester (2020). readr: Read Rectangular Text Data. R package version 1.4.0. https://CRAN.R-project.org/package=readr
[5] C. Sievert. Interactive Web-Based Data Visualization with R, plotly, and shiny. Chapman and Hall/CRC Florida, 2020.
[6] Wickham et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686
[7] Garrett Grolemund, Hadley Wickham (2011). Dates and Times Made Easy with lubridate. Journal of Statistical Software, 40(3), 1-25. URL https://www.jstatsoft.org/v40/i03/.
[8] H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.
[9] Erich Neuwirth (2014). RColorBrewer: ColorBrewer Palettes. R package version 1.1-2. https://CRAN.R-project.org/package=RColorBrewer
[10] Ron Ammar (2019). randomcoloR: Generate Attractive Random Colors. R package version 1.1.0.1. https://CRAN.R-project.org/package=randomcoloR
[11] Jennifer Bryan (2017). gapminder: Data from Gapminder. R package version 0.3.0. https://CRAN.R-project.org/package=gapminder
[12] Karthik Ram and Hadley Wickham (2018). wesanderson: A Wes Anderson Palette Generator. R package version 0.3.6. https://CRAN.R-project.org/package=wesanderson
[13 Townsville City Council Building Approvals - data.gov.au. (2021). Retrieved 2 June 2021, from https://data.gov.au/data/dataset/tcc-building-approvals
[14] Townsville Suburbs - data.gov.au. (2021). Retrieved 2 June 2021, from https://data.gov.au/dataset/ds-dga-81cbbedc-e35f-4266-980d-21a6159b2404/distribution/dist-dga-28812258-4cf4-46aa-aa43-0206d7c60920/details?q=
[15] RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/.
[16] GitHub: Where the world builds software. (2021). Retrieved 2 June 2021, from https://github.com/
[17] GitKraken Documentation. (2021). Retrieved 2 June 2021, from https://support.gitkraken.com/start-here/guide/
[18] A hackable text editor for the 21st Century. (2021). Retrieved 2 June 2021, from https://atom.io
[19] Azyyati Marzukhi, M., Jaafar, A. and Ling Hoon Leh, O., 2019. The Effectiveness Of Building Plan Approval. Case Study: Subang Jaya Municipal Council, Selangor. [online] Malaysia. Available at: https://www.matec-conferences.org/articles/matecconf/pdf/2019/15/matecconf_iconbee2019_06005.pdf [Accessed 2 June 2021].